V. S. Abhijith, C. V. Anoop, S. Venugopal, Titto Thomas, K. Vineeth, K. Reshma
This paper proposes one such strategy where the emphasis is on imparting knowledge with the help of technology. The strategy proposes a well balanced combination of directed approaches like vocal explanations, videos and constructivist approaches like interactive flash games, hands on experiments which help to impart knowledge to students. The focus is more on imparting knowledge rather than the extensive use of technology. The scheme not only uses technology, but also gives emphasis on conventional teaching methods as and when required. The proposed strategy was successfully tested in four rural schools in the state of Kerala, India.
{"title":"Powering Imagination: An Initiative for Technology Enhanced Learning in Rural Schools","authors":"V. S. Abhijith, C. V. Anoop, S. Venugopal, Titto Thomas, K. Vineeth, K. Reshma","doi":"10.1109/T4E.2014.55","DOIUrl":"https://doi.org/10.1109/T4E.2014.55","url":null,"abstract":"This paper proposes one such strategy where the emphasis is on imparting knowledge with the help of technology. The strategy proposes a well balanced combination of directed approaches like vocal explanations, videos and constructivist approaches like interactive flash games, hands on experiments which help to impart knowledge to students. The focus is more on imparting knowledge rather than the extensive use of technology. The scheme not only uses technology, but also gives emphasis on conventional teaching methods as and when required. The proposed strategy was successfully tested in four rural schools in the state of Kerala, India.","PeriodicalId":151911,"journal":{"name":"2014 IEEE Sixth International Conference on Technology for Education","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114784739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Krishnaswamy, Asif Qamar, R. Krishnan, Krishnakumar Rajagopal, Naveen Narayan, K. Bijlani, K. Moudgalya
Jnana Edge provides a fundamentally different approach to bringing a knowledge experience, in a qualitatively rich, focused way to specific demographics. This is done through an interdisciplinary convergence of key technological advancements from scalable hierarchical system architectures, cloud computing, dynamic cache hierarchies, and distributed virtualization. Architecture and implementation considerations are presented, particularly for Buddhi Edge which instantiates the Jnana Edge framework in the educational scope. Future directions are also suggested.
{"title":"Bringing Knowledge to the Edge with Jnana Edge and Buddhi Edge: Architecture, Implementation, and Future Directions","authors":"D. Krishnaswamy, Asif Qamar, R. Krishnan, Krishnakumar Rajagopal, Naveen Narayan, K. Bijlani, K. Moudgalya","doi":"10.1109/T4E.2014.35","DOIUrl":"https://doi.org/10.1109/T4E.2014.35","url":null,"abstract":"Jnana Edge provides a fundamentally different approach to bringing a knowledge experience, in a qualitatively rich, focused way to specific demographics. This is done through an interdisciplinary convergence of key technological advancements from scalable hierarchical system architectures, cloud computing, dynamic cache hierarchies, and distributed virtualization. Architecture and implementation considerations are presented, particularly for Buddhi Edge which instantiates the Jnana Edge framework in the educational scope. Future directions are also suggested.","PeriodicalId":151911,"journal":{"name":"2014 IEEE Sixth International Conference on Technology for Education","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116807363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
LEMA (Learning Environment for Modeling Abilities) is an ICT based tool developed in order to promote students' modeling abilities such as developing explanations of phenomena based on microscopic models, predicting the outcome of new phenomena and revising explanations in the light of experimental evidence. It is developed for the context of self study. In a prior study, we have reported that students learning with LEMA showed statistically significant difference in their learning outcomes on a modeling ability based test than the control group. While we know that LEMA helped develop students modeling skills, the prior study did not address how it helped or why. In order to gain insight into this, in this study we investigate the different paths that different learners take as they interact with LEMA. Using screen capture logs of students' interaction with LEMA, we characterize the difference in behavior between students who score low and students who score high in a modeling based post test. We find that in spite of the fact that the total time spent by all students while interacting with LEMA is the same, the duration of time spent on each feature of LEMA and the action taken within, varies for high and low scorers.
LEMA (Learning Environment for Modeling Abilities)是一种基于ICT的工具，旨在提高学生的建模能力，如基于微观模型对现象进行解释，预测新现象的结果以及根据实验证据修改解释。它是为自学而开发的。在之前的一项研究中，我们报道了使用LEMA学习的学生在基于建模能力的测试中与对照组的学习结果有统计学上的显著差异。虽然我们知道LEMA有助于培养学生的建模技能，但之前的研究并没有说明它是如何起作用的或为什么起作用的。为了深入了解这一点，在本研究中，我们调查了不同学习者在与LEMA互动时采取的不同途径。利用学生与LEMA互动的屏幕截图日志，我们描述了在基于建模的后测试中得分低的学生和得分高的学生之间的行为差异。我们发现，尽管所有学生在与LEMA互动时所花费的总时间是相同的，但高分和低分学生在LEMA的每个特征上所花费的时间和所采取的行动是不同的。
{"title":"A Self Study Learning Environment for Modeling Abilities: Do All Learners Take the Same Learning Path?","authors":"Anura Kenkre, S. Murthy","doi":"10.1109/T4E.2014.8","DOIUrl":"https://doi.org/10.1109/T4E.2014.8","url":null,"abstract":"LEMA (Learning Environment for Modeling Abilities) is an ICT based tool developed in order to promote students' modeling abilities such as developing explanations of phenomena based on microscopic models, predicting the outcome of new phenomena and revising explanations in the light of experimental evidence. It is developed for the context of self study. In a prior study, we have reported that students learning with LEMA showed statistically significant difference in their learning outcomes on a modeling ability based test than the control group. While we know that LEMA helped develop students modeling skills, the prior study did not address how it helped or why. In order to gain insight into this, in this study we investigate the different paths that different learners take as they interact with LEMA. Using screen capture logs of students' interaction with LEMA, we characterize the difference in behavior between students who score low and students who score high in a modeling based post test. We find that in spite of the fact that the total time spent by all students while interacting with LEMA is the same, the duration of time spent on each feature of LEMA and the action taken within, varies for high and low scorers.","PeriodicalId":151911,"journal":{"name":"2014 IEEE Sixth International Conference on Technology for Education","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114256788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An active learning strategy implemented in engineering classes is presented here. This method incorporates the benefits of flipped-classroom learning and quiz, but with few differences. This method is implemented in larger engineering classes of two different branches and two different years. The method of implementation and observations are presented. The relative advantages and cautioning for this method are also discussed.
{"title":"Flip Class Based Group Quiz: Observations from Engineering Classes","authors":"A. Sadiq","doi":"10.1109/T4E.2014.45","DOIUrl":"https://doi.org/10.1109/T4E.2014.45","url":null,"abstract":"An active learning strategy implemented in engineering classes is presented here. This method incorporates the benefits of flipped-classroom learning and quiz, but with few differences. This method is implemented in larger engineering classes of two different branches and two different years. The method of implementation and observations are presented. The relative advantages and cautioning for this method are also discussed.","PeriodicalId":151911,"journal":{"name":"2014 IEEE Sixth International Conference on Technology for Education","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121776972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Grivokostopoulou, I. Perikos, I. Hatzilygeroudis
Utilization of semantic web technologies in educational systems is rapidly expanded, bringing new and more efficient teaching and learning capabilities. Semantic Web Based Educational Systems (SWBEs) rely on semantic web technologies and are proved to be more intelligent and personalized to the students learning needs. In this paper, we present a semantic web based adaptive educational system that is developed to assist the students in learning the challenging subjects of the Artificial Intelligence course. The system utilizes ontologies to represent the domain of the course's curriculum and the student model. Also, the Semantic Web Rule Language (SWRL) rules are used for making decisions on the learning activities to propose to the student according to his/her profile and knowledge level. The evaluation results indicate quite promising performance regarding the system's learning capabilities and functionality.
语义网技术在教育系统中的应用正在迅速扩大，带来了新的、更高效的教学能力。基于语义Web的教育系统(Semantic Web Based Educational Systems, SWBEs)是一种基于语义Web技术的教育系统，具有更高的智能化和个性化，能够满足学生的学习需求。在本文中，我们提出了一个基于语义网的自适应教学系统，该系统旨在帮助学生学习人工智能课程中具有挑战性的科目。该系统利用本体来表示课程的课程和学生模型的领域。此外，语义Web规则语言(SWRL)规则用于根据学生的个人资料和知识水平来决定向学生提出的学习活动。评估结果表明，在系统的学习能力和功能方面，该系统的表现相当有希望。
{"title":"Using Semantic Web Technologies in a Web Based System for Personalized Learning AI Course","authors":"F. Grivokostopoulou, I. Perikos, I. Hatzilygeroudis","doi":"10.1109/T4E.2014.36","DOIUrl":"https://doi.org/10.1109/T4E.2014.36","url":null,"abstract":"Utilization of semantic web technologies in educational systems is rapidly expanded, bringing new and more efficient teaching and learning capabilities. Semantic Web Based Educational Systems (SWBEs) rely on semantic web technologies and are proved to be more intelligent and personalized to the students learning needs. In this paper, we present a semantic web based adaptive educational system that is developed to assist the students in learning the challenging subjects of the Artificial Intelligence course. The system utilizes ontologies to represent the domain of the course's curriculum and the student model. Also, the Semantic Web Rule Language (SWRL) rules are used for making decisions on the learning activities to propose to the student according to his/her profile and knowledge level. The evaluation results indicate quite promising performance regarding the system's learning capabilities and functionality.","PeriodicalId":151911,"journal":{"name":"2014 IEEE Sixth International Conference on Technology for Education","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122019193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This work investigates the effectiveness of using program slicing technique along with spoken tutorials to improve comprehension and debugging skills of novice programmers. We also evaluate the programming pattern of the learners while using the program slicing technique. Qualitative and Quantitative studies were conducted using spoken tutorial workshops on Java course. Results of the study have shown improvement in programming competencies and conceptual understanding when subjected to program slicing techniques along with spoken tutorials.
{"title":"Application of Program Slicing Technique to Improve Novice Programming Competency in Spoken Tutorial Workshops","authors":"K. Eranki, K. Moudgalya","doi":"10.1109/T4E.2014.1","DOIUrl":"https://doi.org/10.1109/T4E.2014.1","url":null,"abstract":"This work investigates the effectiveness of using program slicing technique along with spoken tutorials to improve comprehension and debugging skills of novice programmers. We also evaluate the programming pattern of the learners while using the program slicing technique. Qualitative and Quantitative studies were conducted using spoken tutorial workshops on Java course. Results of the study have shown improvement in programming competencies and conceptual understanding when subjected to program slicing techniques along with spoken tutorials.","PeriodicalId":151911,"journal":{"name":"2014 IEEE Sixth International Conference on Technology for Education","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133756802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Chand, P. Murthy, Vivek Gupta, A. Kandasamy, D. Jayarajan, Lakshman Sethu, V. Benegal, M. Varghese, M. Komaromy, Sanjeev Arora
Addiction or Substance Use Disorders (SUD) is a growing public health problem in India. There are very few trained health professionals to provide evidence based care for these conditions. We initiated a weekly tele-ECHO clinic to train health professionals in the recognition and management of Alcohol and tobacco use disorders. The preliminary results points towards the feasibility as well as acceptability of the ECHO model of training in addiction mental health. There is a need for more involvement of the health care providers in future NIMHANS ECHO Programs.
{"title":"Technology Enhanced Learning in Addiction Mental Health: Developing a Virtual Knowledge Network: NIMHANS ECHO","authors":"P. Chand, P. Murthy, Vivek Gupta, A. Kandasamy, D. Jayarajan, Lakshman Sethu, V. Benegal, M. Varghese, M. Komaromy, Sanjeev Arora","doi":"10.1109/T4E.2014.14","DOIUrl":"https://doi.org/10.1109/T4E.2014.14","url":null,"abstract":"Addiction or Substance Use Disorders (SUD) is a growing public health problem in India. There are very few trained health professionals to provide evidence based care for these conditions. We initiated a weekly tele-ECHO clinic to train health professionals in the recognition and management of Alcohol and tobacco use disorders. The preliminary results points towards the feasibility as well as acceptability of the ECHO model of training in addiction mental health. There is a need for more involvement of the health care providers in future NIMHANS ECHO Programs.","PeriodicalId":151911,"journal":{"name":"2014 IEEE Sixth International Conference on Technology for Education","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129527252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Reforms in the educational system emphasize more on continuous assessment. The descriptive examination question paper when compared to objective question paper acts as a better aid in continuous assessment for testing the progress of a student under various cognitive levels at different stages of learning. Unfortunately, assessment of descriptive answers is found to be tedious and time consuming by instructors due to the increase in number of examinations in continuous assessment system. In this paper, an attempt has been made to address the problem of automatic evaluation of descriptive answer using vector based similarity matrix with order based word-to-word syntactic similarity measure. Word order similarity measure remains as one of the best measure to find the similarity between sequential words in sentences and is increasing its popularity due to its simple interpretation and easy computation. To the best of our knowledge no work has been carried out for automatic evaluation of descriptive answer using word order vectors. The experimental results prove that this approach is promising for application in automatic evaluation of descriptive answer paper.
{"title":"Use of Syntactic Similarity Based Similarity Matrix for Evaluating Descriptive Answer","authors":"D. V. Paul, J. Pawar","doi":"10.1109/T4E.2014.60","DOIUrl":"https://doi.org/10.1109/T4E.2014.60","url":null,"abstract":"Reforms in the educational system emphasize more on continuous assessment. The descriptive examination question paper when compared to objective question paper acts as a better aid in continuous assessment for testing the progress of a student under various cognitive levels at different stages of learning. Unfortunately, assessment of descriptive answers is found to be tedious and time consuming by instructors due to the increase in number of examinations in continuous assessment system. In this paper, an attempt has been made to address the problem of automatic evaluation of descriptive answer using vector based similarity matrix with order based word-to-word syntactic similarity measure. Word order similarity measure remains as one of the best measure to find the similarity between sequential words in sentences and is increasing its popularity due to its simple interpretation and easy computation. To the best of our knowledge no work has been carried out for automatic evaluation of descriptive answer using word order vectors. The experimental results prove that this approach is promising for application in automatic evaluation of descriptive answer paper.","PeriodicalId":151911,"journal":{"name":"2014 IEEE Sixth International Conference on Technology for Education","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122359743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Radhamani, Hemalatha Sasidharakurup, D. Kumar, Nijin Nizar, B. Nair, K. Achuthan, Shyam Diwakar
Virtual laboratories are ICT tools that are becoming more prevalent in classroom education complementing the lack of resources or tutors while enabling anytime-anywhere student participation scenarios. Specifically disciplines such as biotechnology, which are interaction rich, have seen several types of virtual labs. In this paper, we explore an analysis of student feedback post virtual labs sessions suggesting virtual labs improve teaching and learning experiences via user-interactions. Feedback was collected from undergraduate and postgraduate level students belonging to biotechnology programs. We look at two objectives namely perceived usefulness and the role of interactions on the virtual platform and simulators, in addition to animations. Most data were collected using direct approach via organized workshops. This approach allowed us to extract useful information without concerns of sparseness and unsolicited data compared to remote feedback. Our studies on feedback analysis indicate that student users interpret results in animation based virtual labs. However, a larger percentage of users suggest student usage and performance improved only with interactive simulators rather than animations. Although further tests are being performed, our preliminary studies on 200 participants suggest novel virtual labs models must include a simulation or emulations of lab environment in order to enhance student laboratory skills.
{"title":"Explicit Interactions by Users Form a Critical Element in Virtual Labs Aiding Enhanced Education -- A Case Study from Biotechnology Virtual Labs","authors":"R. Radhamani, Hemalatha Sasidharakurup, D. Kumar, Nijin Nizar, B. Nair, K. Achuthan, Shyam Diwakar","doi":"10.1109/T4E.2014.37","DOIUrl":"https://doi.org/10.1109/T4E.2014.37","url":null,"abstract":"Virtual laboratories are ICT tools that are becoming more prevalent in classroom education complementing the lack of resources or tutors while enabling anytime-anywhere student participation scenarios. Specifically disciplines such as biotechnology, which are interaction rich, have seen several types of virtual labs. In this paper, we explore an analysis of student feedback post virtual labs sessions suggesting virtual labs improve teaching and learning experiences via user-interactions. Feedback was collected from undergraduate and postgraduate level students belonging to biotechnology programs. We look at two objectives namely perceived usefulness and the role of interactions on the virtual platform and simulators, in addition to animations. Most data were collected using direct approach via organized workshops. This approach allowed us to extract useful information without concerns of sparseness and unsolicited data compared to remote feedback. Our studies on feedback analysis indicate that student users interpret results in animation based virtual labs. However, a larger percentage of users suggest student usage and performance improved only with interactive simulators rather than animations. Although further tests are being performed, our preliminary studies on 200 participants suggest novel virtual labs models must include a simulation or emulations of lab environment in order to enhance student laboratory skills.","PeriodicalId":151911,"journal":{"name":"2014 IEEE Sixth International Conference on Technology for Education","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129127300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Eye-tracking technology is being increasingly used in science, technology, engineering and mathematics (STEM) education research. However, most available eye-tracking devices are oriented towards research problems focusing on attention, particularly in areas such as advertising, linguistics, human factors, human-computer interaction, training simulators, sports and virtual reality. Problems in these areas are fundamentally different from those in STEM education, where attention is only one of the many important variables in teaching-learning. Since learning is a process happening over time, STEM investigations focus on understanding the learning process, and this requires moving beyond attention information, doing sophisticated analysis of fixation data, and ways of collecting richer data that support such process analysis. In this paper, we present our difficulties and experiences in using standard eye-tracking systems to understand the learning process. We also describe some new methods developed to collect and analyze process data, and propose several possible extensions to eye tracking systems that would make eye tracking more useful for STEM education research.
{"title":"Eye-Tracking in STEM Education Research: Limitations, Experiences and Possible Extensions","authors":"Prajakt Pande, S. Chandrasekharan","doi":"10.1109/T4E.2014.29","DOIUrl":"https://doi.org/10.1109/T4E.2014.29","url":null,"abstract":"Eye-tracking technology is being increasingly used in science, technology, engineering and mathematics (STEM) education research. However, most available eye-tracking devices are oriented towards research problems focusing on attention, particularly in areas such as advertising, linguistics, human factors, human-computer interaction, training simulators, sports and virtual reality. Problems in these areas are fundamentally different from those in STEM education, where attention is only one of the many important variables in teaching-learning. Since learning is a process happening over time, STEM investigations focus on understanding the learning process, and this requires moving beyond attention information, doing sophisticated analysis of fixation data, and ways of collecting richer data that support such process analysis. In this paper, we present our difficulties and experiences in using standard eye-tracking systems to understand the learning process. We also describe some new methods developed to collect and analyze process data, and propose several possible extensions to eye tracking systems that would make eye tracking more useful for STEM education research.","PeriodicalId":151911,"journal":{"name":"2014 IEEE Sixth International Conference on Technology for Education","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127137393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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